摘要:
The various embodiments described herein include methods, devices, and systems for categorizing motion events. In one aspect, a method is performed at a camera device. The method includes: (1) capturing a plurality of video frames via the image sensor, the plurality of video frames corresponding to a scene in a field of view of the camera; (2) sending the video frames to the remote server system in real-time; (3) while sending the video frames to the remote server system in real-time: (a) determining that motion has occurred within the scene; (b) in response to determining that motion has occurred within the scene, characterizing the motion as a motion event; and (c) generating motion event metadata for the motion event; and (4) sending the generated motion event metadata to the remote server system concurrently with the video frames.
摘要:
The various embodiments described herein include methods, devices, and systems for categorizing motion events. In one aspect, a method includes: (1) obtaining a plurality of video frames, the plurality of video frames corresponding to a scene and a motion event candidate; (2) identifying one or more visual characteristics of the scene; (3) obtaining one or more background factors for the scene; (4) utilizing the obtained background factors to identify one or more motion entities; (5) for each identified motion entity: (a) classifying the motion entity by performing object recognition; and (b) obtaining one or more representative motion vectors based on a motion track of the motion entity; and (6) assigning a motion event category to the motion event candidate based on the identified visual characteristics, the obtained background factors, the classified motion entities, and the obtained representative motion vectors.
摘要:
The disclosed technology includes techniques for improved content coverage in automatically-generated content summaries. The technique may include clustering a set of input content, determining diffusion for each cluster, and selecting representatives of each cluster to optimize other secondary metrics. Various types of input content may be used, including groups of images, video clips, or other multimedia content. Contiguous content may be manually or programmatically divided into discrete portions before clustering, for example, a lengthy video divided into a number of short clips. In some implementations, the disclosed technique may be implemented effectively on a mobile device. In other words, the processing required may be computationally feasible for execution on a smartphone or similar device.
摘要:
The various embodiments described herein include methods, devices, and systems for categorizing motion events. In one aspect, a method includes: (1) obtaining a plurality of video frames, the plurality of video frames corresponding to a scene and a motion event candidate; (2) identifying one or more visual characteristics of the scene; (3) obtaining one or more background factors for the scene; (4) utilizing the obtained background factors to identify one or more motion entities; (5) for each identified motion entity: (a) classifying the motion entity by performing object recognition; and (b) obtaining one or more representative motion vectors based on a motion track of the motion entity; and (6) assigning a motion event category to the motion event candidate based on the identified visual characteristics, the obtained background factors, the classified motion entities, and the obtained representative motion vectors.
摘要:
The various embodiments described herein include methods, devices, and systems for analyzing video streams. In one aspect, a method includes, while receiving a video stream: obtaining motion start information indicating that a portion of the video stream includes a motion event candidate; and segmenting the portion of the video stream into a plurality of segments including an initial segment. The method also includes obtaining a first categorization for the motion event candidate based on the initial segment; and, in accordance with the obtained first categorization, generating a log entry for the motion event candidate including the first categorization. The method further includes: in response to obtaining motion end information, obtaining a second categorization for the motion event based on the plurality of segments; and updating the log entry for the motion event candidate based on the obtained second categorization.
摘要:
A computer-implemented technique can receive, at a computing device including one or more processors, a plurality of photos. The technique can extract quality features and similarity features for each of the plurality of photos and can obtain weights for the various quality features and similarity features based on an analysis of a reference photo collection. The technique can generate a quality metric for each of the plurality of photos and can generate a similarity matrix for the plurality of photos by analyzing the various quality features and similarity features and using the obtained weights. The technique can perform joint global maximization of photo quality and photo diversity using the quality metrics and the similarity matrix in order to select a subset of the plurality of photos having a high degree of representativeness. The technique can then store the subset of the plurality of photos in a memory.
摘要:
Certain embodiments of the disclosed technology include systems and methods for determining the priority of a notification on a mobile device using machine learning. Other aspects of the disclosed technology include selectively displaying notifications based on the priority of a notification. According to an embodiment of the disclosed technology, a computer-implement method is provided that comprises outputting, to a display device operatively coupled to a mobile device, a plurality of notifications, wherein each respective notification from the plurality of notifications is associated with a respective priority score; modifying, by the mobile device, a ranking model based on a user input received responsive to a first notification from the plurality of notifications and a characteristic of a second notification from the plurality of notifications; determining, by the mobile device, a priority score associated with a third notification based on the modified ranking model; and outputting, to the display device, the third notification based on the priority score associated with the third notification, wherein the third notification is graphically emphasized responsive to the priority score associated with the third notification being greater than at least one respective priority score associated with a corresponding respective notification from the plurality of notifications.
摘要:
Certain embodiments of the disclosed technology include systems and methods for determining the priority of a notification on a mobile device using machine learning. Other aspects of the disclosed technology include selectively displaying notifications based on the priority of a notification. According to an embodiment of the disclosed technology, a computer-implement method is provided that comprises outputting, to a display device operatively coupled to a mobile device, a plurality of notifications, wherein each respective notification from the plurality of notifications is associated with a respective priority score; modifying, by the mobile device, a ranking model based on a user input received responsive to a first notification from the plurality of notifications and a characteristic of a second notification from the plurality of notifications; determining, by the mobile device, a priority score associated with a third notification based on the modified ranking model; and outputting, to the display device, the third notification based on the priority score associated with the third notification, wherein the third notification is graphically emphasized responsive to the priority score associated with the third notification being greater than at least one respective priority score associated with a corresponding respective notification from the plurality of notifications.
摘要:
Techniques for determining motion saliency in video content using center-surround receptive fields. In some implementations, images or frames from a video may be apportioned into non-overlapped regions, for example, by applying a rectilinear grid. For each grid region, or cell, motion consistency may be measured between the center and surround area of that cell across frames of the video. Consistent motion across the center-surround area may indicate that the corresponding region has low variation. The larger the difference between center-surround motions in a cell, the more likely the region has high motion saliency.
摘要:
Certain embodiments of the disclosed technology include systems and methods for determining the priority of a notification on a mobile device using machine learning. Other aspects of the disclosed technology include selectively displaying notifications based on the priority of a notification. According to an embodiment of the disclosed technology, a computer-implement method is provided that comprises outputting, to a display device operatively coupled to a mobile device, a plurality of notifications, wherein each respective notification from the plurality of notifications is associated with a respective priority score; modifying, by the mobile device, a ranking model based on a user input received responsive to a first notification from the plurality of notifications and a characteristic of a second notification from the plurality of notifications; determining, by the mobile device, a priority score associated with a third notification based on the modified ranking model; and outputting, to the display device, the third notification based on the priority score associated with the third notification, wherein the third notification is graphically emphasized responsive to the priority score associated with the third notification being greater than at least one respective priority score associated with a corresponding respective notification from the plurality of notifications.